Reading songs : a computational analysis of popular songs lyrics

There is no doubt that certain songs are so easily liked by the public because of their melody. However, certain songs strike us for their lyrics, either because they convey an important (for us) meaning, or for their captivating sound when sung. Since the year 1958, the Billboard magazine held the special section Hot 100, with a rank of the 100 most popular songs of the week. Exploiting this invaluable source regarding the musical taste of the past decades until our days, we perform an analysis over various aspects of popular songs lyrics, especially focusing on the question: what is the importance of lyrics, when classifying musical artists and genres? We find out that, as we expected, many artists are not immediately recognizable only by their lyrics; some of them, however, and especially if they belong to some specific genres (such as rap), stand out, opening to the possibility of further analysis over their styles and theme

Data-Driven Control and Data-Poisoning attacks in Buildings: the KTH Live-In Lab case study

This work investigates the feasibility of using input-output data-driven control techniques for building control and their susceptibility to data-poisoning techniques. The analysis is performed on a digital replica of the KTH Livein Lab, a non-linear validated model representing one of the KTH Live-in Lab building testbeds. This work is motivated by recent trends showing a surge of interest in using data-based techniques to control cyber-physical systems. We also analyze the susceptibility of these controllers to data-poisoning methods, a particular type of machine learning threat geared towards finding imperceptible attacks that can undermine the performance of the system under consideration. We consider the Virtual Reference Feedback Tuning (VRFT), a popular data-driven control technique, and show its performance on the KTH Live-In Lab digital replica. We then demonstrate how poisoning attacks can be crafted and illustrate the impact of such attacks. Numerical experiments reveal the feasibility of using data-driven control methods for finding efficient control laws. However, a subtle change in the datasets can significantly deteriorate the performance of VRFT

Osteolytic vs. Osteoblastic Metastatic Lesion: Computational Modeling of the Mechanical Behavior in the Human Vertebra after Screws Fixation Procedure

Metastatic lesions compromise the mechanical integrity of vertebrae, increasing the fracture risk. Screw fixation is usually performed to guarantee spinal stability and prevent dramatic fracture events. Accordingly, predicting the overall mechanical response in such conditions is critical to planning and optimizing surgical treatment. This work proposes an image-based finite element computational approach describing the mechanical behavior of a patient-specific instrumented metastatic vertebra by assessing the effect of lesion size, location, type, and shape on the fracture load and fracture patterns under physiological loading conditions. A specific constitutive model for metastasis is integrated to account for the effect of the diseased tissue on the bone material properties. Computational results demonstrate that size, location, and type of metastasis significantly affect the overall vertebral mechanical response and suggest a better way to account for these parameters in estimating the fracture risk. Combining multiple osteolytic lesions to account for the irregular shape of the overall metastatic tissue does not significantly affect the vertebra fracture load. In addition, the combination of loading mode and metastasis type is shown for the first time as a critical modeling parameter in determining fracture risk. The proposed computational approach moves toward defining a clinically integrated tool to improve the management of metastatic vertebrae and quantitatively evaluate fracture risk

The Lack of Systemic and Subclinical Side Effects of Botulinum Neurotoxin Type-A in Patients Affected by Post-Stroke Spasticity: A Longitudinal Cohort Study

Botulinum Neurotoxin type-A (BoNT-A) is the treatment of choice for focal post-stroke spasticity (PSS). Due to its mechanism of action and the administration method, some authors raised concern about its possible systemic diffusion leading to contralateral muscle weakness and autonomic nervous system (ANS) alterations. Stroke itself is a cause of motor disability and ANS impairment; therefore, it is mandatory to prevent any source of additional loss of strength and adjunctive ANS disturbance. We enrolled 15 hemiparetic stroke survivors affected by PSS already addressed to BoNT-A treatment. Contralateral handgrip strength and ANS parameters, such as heart rate variability, impedance cardiography values, and respiratory sinus arrythmia, were measured 24 h before (T0) and 10 days after (T1) the ultrasound (US)-guided BoNT-A injection. At T1, neither strength loss nor modification of the basal ANS patterns were found. These findings support recent literature about the safety profile of BoNT-A, endorsing the importance of the US guide for a precise targeting and the sparing of "critical" structures as vessels and nerves

A deep learning approach for the 3D reconstruction of dust density and temperature in star-forming regions

Funding: The team in Heidelberg acknowledges funding from the European Research Council via the ERC Synergy Grant “ECOGAL” (project ID 855130), from the German Excellence Strategy via the Heidelberg Cluster of Excellence (EXC 2181 - 390900948) “STRUCTURES”, and from the German Ministry for Economic Affairs and Climate Action in project “MAINN” (funding ID 50OO2206). They also thank for computing resources provided by The Länd and DFG through grant INST 35/1134-1 FUGG and for data storage at SDS@hd through grant INST 35/1314-1 FUGG.Aims. We introduce a new deep learning approach for the reconstruction of 3D dust density and temperature distributions from multi-wavelength dust emission observations on the scale of individual star-forming cloud cores (< 0.2 pc). Methods. We construct a training data set by processing cloud cores from the Cloud Factory simulations with the POLARIS radiative transfer code to produce synthetic dust emission observations at 23 wavelengths between 12 and 1300 µm. We simplify the task by reconstructing the cloud structure along individual lines of sight and train a conditional invertible neural network (cINN) for this purpose. The cINN belongs to the group of normalising flow methods and is able to predict full posterior distributions for the target dust properties. We test different cINN setups, ranging from a scenario that includes all 23 wavelengths down to a more realistically limited case with observations at only seven wavelengths. We evaluate the predictive performance of these models on synthetic test data. Results. We report an excellent reconstruction performance for the 23-wavelengths cINN model, achieving median absolute relative errors of about 1.8% in log(ndust/m−3) and 1% in log(Tdust/K), respectively. We identify trends towards overestimation at the low end of the density range and towards underestimation at the high end of both density and temperature, which may be related to a bias in the training data. Limiting coverage to a combination of only seven wavelengths, we still find a satisfactory performance with average absolute relative errors of about 3.3% and 2.5% in log(ndust/m−3) and log(Tdust/K). Conclusions. This proof of concept study shows that the cINN-based approach for 3D reconstruction of dust density and temperature is very promising and even feasible under realistic observational constraints.Peer reviewe

An SMA and HERSCHEL view of the HMSFR G23.01-0.41

We present here the results of our recent SMA observations at 1.3 mm toward the high-mass star-forming region (HMSFR) G23.01-0.41, with both the most extended and compact array configurations, providing sub-arcsecond and high sensitivity maps for different molecular lines (e.g., 12CO and isotopomers, SiO, CH3CN, and CH3OH). We also complement this dataset with the spectral energy distribution (SED) between 3.4 μm and 1.1 mm and the continuum images from the Hi-GAL/Herschel survey. The aim of these observations is twofold: 1) to image at high angular and spectral resolution the flattened, hot molecular core (HMC) detected toward G23.01-0.41, which contains strong masers and a radio continuum source; 2) to compare the spatial distribution and velocity field of the gas close to the central YSO with those of the associated molecular outflow. The dust and molecular line emission trace a flattened structure inside a radius of 8000 AU from the center of radio continuum and maser line emission in the region. The equatorial plane of this HMC is strictly perpendicular to the main elongation of the outflow emission onto the plane of the sky, which extends over a ten times larger region (~0.5 pc). The inner velocity field mapped with the CH3CN (12K-11K) lines outlines that molecular gas rotates about the outflow axis and is simultaneously dragged along the outflow direction indicating Hubble-law expansion. The IR SED from the HMC suggests the presence of a single O9.5 ZAMS star with a mass ~19 M⊙, consistent with the mass required for centrifugal equilibrium

F9 Missense mutations impairing factor ix activation are associated with pleiotropic plasma phenotypes

Background: Circulating dysfunctional factor IX (FIX) might modulate distribution of infused FIX in haemophilia B (HB) patients. Recurrent substitutions at FIX activation sites (R191-R226, &gt;300 patients) are associated with variable FIX activity and antigen (FIXag) levels. Objectives: To investigate i) expression of a complete panel of missense mutations at FIX activation sites and ii) contribution of F9 genotypes on the FIX pharmacokinetics (PK). Methods: FIXag and activity assays in plasma and after recombinant expression of FIX variants. Analysis of infused FIX PK parameters in patients (n=30), mostly enrolled in the F9 Genotype and PK HB Italian Study (GePKHIS; EudraCT ID2017-003902-42). Results: The variable FIXag amounts and good relation between biosynthesis and activity of multiple R191 variants result in graded moderate-to-mild severity of the R191C&gt;L&gt;P&gt;H substitutions. Recombinant expression may predict the absence in the HB mutation database of the benign R191Q/W/K and R226K substitutions. Equivalent changes at R191/R226 produced higher FIXag levels for R226Q/W/P substitutions, as also observed in p.R226W female carrier plasma. PK analysis in patients suggested that infused FIX Alpha distribution and Beta elimination phases positively correlated with endogenous FIXag levels. Mean residence time was particularly prolonged (79.4 hrs, 95% CI 44.3-114.5) in patients (n=7) with the R191/R226 substitutions, which in regression analysis were independent predictors (β coefficient 0.699, p=0.004) of Beta half-life, potentially prolonged by the increasing over time ratio between endogenous and infused FIX. Conclusions: FIXag levels and specific features of the dysfunctional R191/R226 variants may exert pleiotropic effects both on HB patients’ phenotypes and substitutive treatment

The Galactic dynamics revealed by the filamentary structure in atomic hydrogen emission

Funding: J.D.S., R.K.S., and S.C.O.G. are funded by the European Research Council via the ERC Synergy Grant “ECOGAL – Understanding our Galactic ecosystem: From the disk of the Milky Way to the formation sites of stars and planets” (project ID 855130). R.J.S. acknowledges funding from an STFC ERF (grant ST/N00485X/1) and HPC from the DiRAC facility (ST/P002293/1).We present a study of the filamentary structure in the atomic hydrogen (HI) emission at the 21 cm wavelength toward the Galactic plane using the observations in the HI4PI survey. Using the Hessian matrix method across radial velocity channels, we identified the filamentary structures and quantified their orientations using circular statistics. We found that the regions of the Milky Way's disk beyond 10 kpc and up to roughly 18 kpc from the Galactic center display HI filamentary structures predominantly parallel to the Galactic plane. For regions at lower Galactocentric radii, we found that the HI filaments are mostly perpendicular or do not have a preferred orientation with respect to the Galactic plane. We interpret these results as the imprint of supernova feedback in the inner Galaxy and Galactic rotation in the outer Milky Way. We found that the HI filamentary structures follow the Galactic warp and that they highlight some of the variations interpreted as the effect of the gravitational interaction with satellite galaxies. In addition, the mean scale height of the filamentary structures is lower than that sampled by the bulk of the HI emission, thus indicating that the cold and warm atomic hydrogen phases have different scale heights in the outer galaxy. Finally, we found that the fraction of the column density in HI filaments is almost constant up to approximately 18 kpc from the Galactic center. This is possibly a result of the roughly constant ratio between the cold and warm atomic hydrogen phases inferred from the HI absorption studies. Our results indicate that the HI filamentary structures provide insight into the dynamical processes shaping the Galactic disk. Their orientations record how and where the stellar energy input, the Galactic fountain process, the cosmic ray diffusion, and the gas accretion have molded the diffuse interstellar medium in the Galactic plane.Peer reviewe

Bayesian Data-Driven approach enhances synthetic flood loss models

Flood loss estimation models are developed using synthetic or empirical approaches. The synthetic approach consists of what-if scenarios developed by experts. The empirical models are based on statistical analysis of empirical loss data. In this study, we propose a novel Bayesian Data-Driven approach to enhance established synthetic models using available empirical data from recorded events. For five case studies in Western Europe, the resulting Bayesian Data-Driven Synthetic (BDDS) model enhances synthetic model predictions by reducing the prediction errors and quantifying the uncertainty and reliability of loss predictions for post-event scenarios and future events. The performance of the BDDS model for a potential future event is improved by integration of empirical data once a new flood event affects the region. The BDDS model, therefore, has high potential for combining established synthetic models with local empirical loss data to provide accurate and reliable flood loss predictions for quantifying future risk